Alternative Route Optimization

Consumer navigation systems give us the ‘best’ route, which is often defined by time: how do I get there fastest? There are some slight modifications (toll/no toll), but time optimization is typical, and rightly so.

But we are starting to see some new things appear that will change our routing options: more available data fields that make possible alternative route optimization (A.R.O.) and more user interest in routing based on something other than a time model.

A few useful (and hypothetical) examples of how you might want to optimize your route:

• Safety optimization: I want to commute to work in a flow of traffic with drivers who have the lowest number of points on their license.
• Consumer optimization: My coffee-loving cousin is in town and I want to drive a route that exposes us to the highest-rated cafes.
• Health optimization: I want a route with the lowest possible carbon exposure.
• Visual optimization: Route me along a path with the highest-rated Instagram photos tagged with #landscape.
• Bicycle optimization: I want a bicycling route that avoids intersections with a history of high car/bicycle collisions (this example courtesy Eric Nakagawa).

Right now our primary cost model for routing is valued in minutes, but I expect we will see a lot of change in this over the coming years. Some startups working on route optimization are Foxtrot Systems, Routific, Routist (recently bought by Fleetmatics) and I know of a number of teams who are planning on getting into the space.